More Survival Data Mining of Multiple Time of Endpoints

Abstract

Survival analysis is almost always reserved for an endpoint of mortality or recurrence. (Mantel, 1966) However, it can be used for many different types of endpoints as the survival distribution is defined as the time to an event. That event can be any endpoint of interest. For patients with chronic diseases, there are many endpoints to examine. For example, patients with diabetes want to avoid organ failure as well as death, and treatments that can prolong the time to organ failure will be beneficial. For patients with resistant infections, treatments that prevent one or multiple recurrences should be explored. Survival data mining differs from survival analysis in that multiple patient events can occur in sequence. The first step in survival data mining is to define an episode of treatment so that the patient events can be found for analysis. It can be thought of as a sequence of survival functions. In this chapter, we will look at the time to a switch in medications, and contrast how prescriptions are given to patients, either following or disregarding treatment guidelines.